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- Tasks: Join our team as a Quant Developer, supporting trading desks and solving innovative problems.
- Company: A global leader in Commodity trading, dealing with Gas, Power, Oil, Metals, and more.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and learning.
- Why this job: Interact with traders, enhance your skills, and make a real impact in a fast-paced setting.
- Qualifications: Experience in Python, multithreading, and financial institutions is essential.
- Other info: Ideal for those eager to learn and thrive in a collaborative atmosphere.
The predicted salary is between 48000 - 72000 £ per year.
Our client is a truly global Commodity trading company who trade both physical and financial commodities including, Gas & Power, Oil, Metals, Agricultural products, and more… We are looking for a Quant Developer to join the team in the London office, supporting the trading desks; and working alongside the Middle Office/Market & Quantitative Risk teams. This is genuine opportunity to interact with the trading team, learn about the business and to be innovative with your problem solving and delivery. The successful candidate will need to demonstrate a strong work ethic, be able to cope with a busy, fast paced environment and be able to communicate effectively across all levels including Traders and Senior Management. The successful candidate will have: Experience of building multithreaded and multi-process Python apps that consume transactional data, transform, store and visualise data, i.e. exposure to: building multithreaded and multi process python systems using frameworks such as Dask, Pandas, Numpy. building web-based GUI’s using Python frameworks such as Dash building Python based REST servers using frameworks such as Fast API writing Docker files, configuring Gitlab CICD pipelines, deploying to Kubernetes designing and optimising SQL Data bases such as MSSQL or Postgres Experience of working in a financial institution on trading / risk or middle office desks possibly with exposure to: Value at risk PnL attribution Capable of taking responsibility for delivering significant projects, in particular Liaising with risk analysts and middle officers to understand and gather requirements Design, development, testing and documenting REQUIRED SKILLS: Python Multi-threading & asynchronous programming Knowledge of commodities/Energy trading Dask, Pandas, Numpy frameworks. Full life cycle development Excellent Communication skills Python web framework (e.g., Flask, Dash) Built RESTful Web APIs41bf1e1f-b16b-4260-a40a-17c77a06fd15
Quantitative Developer - Middle Office/Risk employer: RICHARD JAMES RECRUITMENT SPECIALISTS LTD
Contact Detail:
RICHARD JAMES RECRUITMENT SPECIALISTS LTD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer - Middle Office/Risk
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Dask, Pandas, and Numpy. Consider building a small project or contributing to open-source projects that utilise these frameworks to showcase your skills.
✨Tip Number 2
Network with professionals in the commodities trading sector. Attend industry meetups or webinars where you can connect with current Quant Developers or traders. This could provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with multithreading and asynchronous programming in Python during interviews. Be ready to explain how you've applied these concepts in past projects, particularly in high-pressure environments.
✨Tip Number 4
Demonstrate your understanding of risk management concepts like Value at Risk and PnL attribution. Brush up on these topics and be prepared to discuss how they relate to the role and your previous experiences.
We think you need these skills to ace Quantitative Developer - Middle Office/Risk
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, multithreading, and any relevant frameworks like Dask, Pandas, and Numpy. Emphasise your work in financial institutions and any specific projects related to trading or risk management.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your skills align with the job requirements, particularly your experience in building Python applications and working in fast-paced environments.
Showcase Relevant Projects: If you have worked on projects that involved building web-based GUIs or RESTful APIs, be sure to include these in your application. Describe your role, the technologies used, and the impact of your work.
Highlight Communication Skills: Since effective communication is crucial for this role, provide examples in your application where you successfully liaised with different teams or stakeholders. This could include working with traders or senior management to gather requirements.
How to prepare for a job interview at RICHARD JAMES RECRUITMENT SPECIALISTS LTD
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, especially in building multithreaded applications and using frameworks like Dask, Pandas, and Numpy. Bring examples of your past projects that demonstrate your technical abilities and problem-solving skills.
✨Understand the Trading Environment
Familiarise yourself with the basics of commodity trading and risk management. Being able to speak knowledgeably about concepts like Value at Risk and PnL attribution will show your potential employer that you understand the industry and can communicate effectively with traders and analysts.
✨Demonstrate Effective Communication
Since the role involves liaising with various teams, practice articulating complex technical concepts in a way that non-technical stakeholders can understand. This will highlight your ability to bridge the gap between technical and non-technical teams.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving skills. Think through how you would approach real-world challenges in a fast-paced trading environment, and be ready to explain your thought process clearly.
